Electronic documents convey information in a variety of different manners. That is, information in an electronic document may be organized according to one or more formats; or, information may not be organized all. For example, most spreadsheets tend to organize, or provide, information according to a familiar row-column topology. Although meaningful relationships between the different rows and columns may not be defined, such information is often organized in a pre-defined manner and may be recognized as structured data. Structured data may also take the form of relational databases and data tables and is often made available in a predictable manner. As such, a predefined consistent organization of data may be relied upon when extracting information from an electronic document containing structured data. In other instances, information in electronic documents may be provided without a specified format; such information is generally classified as unstructured information. Unstructured information generally does not have a pre-defined data model or is not organized in a pre-defined manner. Unstructured data tends to be text heavy, may also contain data such as dates and numbers, and is often not predictable or arranged in a predictable format.
Information in an electronic document may also be provided in a semi-structured manner. That is, information in an electronic document may be organized in some manner, but not necessarily according to a consistent predefined or formal format. In some instances, semi-structured information may be provided in a table; however, all columns of a table may not necessarily be required and/or one or more columns may have extra fields or may contain data of varying formats, lengths, and encodings. Therefore, for an entity that wishes to receive this information and later make sense of this information, deciphering how the information is provided and/or extracting the information in a meaningful manner may prove to be difficult and may require large amounts of human verification.